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Smart city article details
| Title | Offloading Approach For Mobile Edge Computing Based On Chaotic Quantum Particle Swarm Optimization Strategy |
|---|---|
| ID_Doc | 39683 |
| Authors | Zhang D.G.; Sun G.X.; Zhang J.; Zhang T.; Yang P. |
| Year | 2023 |
| Published | Journal of Ambient Intelligence and Humanized Computing, 14, 10 |
| DOI | http://dx.doi.org/10.1007/s12652-023-04672-z |
| Abstract | With the development of 5 g, computing-intensive and complex applications in smart-city is growing rapidly. Due to the limited resources of mobile terminal devices in smart-city, new applications have higher requirements for delay, bandwidth, security, and energy consumption. Computation offloading in mobile edge computing (MEC) is effective to reduce delay and energy consumption of Real-time video analysis. An improved chaos quantum-behaved particle swarm optimization (ICQPSO) algorithm is proposed for multi-user and multi-MEC edge Computation offloading scenarios. Compared with other heuristic algorithms, the improved chaos quantum-behaved particle swarm optimization algorithm can effectively reduce the delay and energy consumption of edge computing offloading. Experimental results show that the improved chaotic quantum-behaved particle swarm optimization (ICQPSO) can effectively avoid premature convergence, has stronger global searchability, and can solve multi-dimensional complex NP-hard problems more efficiently. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. |
| Author Keywords | Chaotic quantum particle swarm optimization; Computation offloading; Mobile edge computing; Real-time video analysis |
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